Our goal is to create a laryngeal neuromotor model of adductor spasmodic dysphonia (SD), a chronic and often debilitating vocal disorder. We will achieve this goal by identifying specific motoneuron firing patterns that occur during vocal spasm by applying recently-developed multidimensional electromyographic technologies to laryngeal muscles. A neuromotor model of SD will serve to characterize the disorder at the motor nucleus. Neuromotor models, in turn, facilitate parallel research in fields of neuroimaging and drug treatment. Speech requires the coordinated control of multiple muscles by the central nervous system, from diaphragm to lips - with larynx playing a principal role in the phonatory process. Skeletal muscles are controlled by two mechanisms: the recruitment of motoneurons and modulation of motoneuron firing rates. Characterization of laryngeal muscle control at the level of the motoneuron is important toward our understanding of normal speech motor control and of neurologic speech motor disorders. Although studied for many decades, the cause of spasmodic dysphonia has remained elusive. Findings of neuroimaging, genetics, and physiology - including conventional electromyography - have been inconsistent and therefore inconclusive about the neural underpinnings of SD. Irrespective of the heterogeneity of findings using conventional modalities, the central participant in SD is the vocal spasm, and therefore we turn the fine lens offered by the imaging of multiple motoneuron firing activities upon these spasms. We hypothesize that vocal spasms are characterized by episodic increases in new motoneuron firing activity and that these new activities are disordered in firing rate characteristics with the existing pool and among themselves. We will test this hypothesis by obtaining motoneuron firing plots of an intralaryngeal muscle: thyroarytenoid. Motoneuron firing plots contain firing activities of multiple motoneurons simultaneously and in their correct temporal relations. Features of recruitment, correlation, synchronicity, and oscillation during vocal spasm will be compared to periods of non-spasm and to control features of a normal control population. Neuromuscular disorders that disrupt speech affect a sizeable population and often seriously impair the professional, social and family interactions of the affected individual. In applying recent advances in multi-dimensional physiologic and artificial intelligence technologies, this project will formulate models of vocal motor control at the level of the brainstem that improve our understanding of speech production in the normal population and of a voice disorder called spasmodic dysphonia. Knowledge gained from this research aims to assist the development of drug therapy to treat spasmodic dysphonia and other neuromuscular speech disorders.